A programmable SDN+NFV-based architecture for UAV telemetry monitoring

White, Kyle and Denney, Ewen and Knudson, Matt D. and Marnerides, Angelos and Pezaros, Dimitrios (2017) A programmable SDN+NFV-based architecture for UAV telemetry monitoring. In: 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC) :. IEEE, USA, pp. 522-527. ISBN 9781509061976

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Abstract

The explosive growth in the worldwide use of Unmanned Aerial Vehicles (UAVs) has raised a critical concern with respect to the adequate management of their ad hoc network configuration as required by their mobility management process. As UAVs migrate among ground control stations, associated network services, routing and operational control must also rapidly migrate to ensure a seamless transition. In this paper, we present a novel, lightweight and modular architecture which supports high mobility and situational-awareness through the application of Software Defined Networking (SDN) and Network Function Virtualization (NFV) principles on top of the UAV infrastructure. By combining SDN+NFV programmability we can achieve a robust migration of UAV-related network services, such as network monitoring and anomaly detection as well as smooth UAV migration that confronts high mobility requirements. The proposed container-based monitoring and anomaly detection Network Functions (NFs) as employed within our architecture can be tuned to specific UAV types providing operators better insight during live, high-mobility deployments. We evaluate our architecture against telemetry from over 80 flights from a scientific research UAV infrastructure showing our ability to tune and detect emerging challenges.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
85200
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Deposited On:
10 Mar 2017 13:18
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Oct 2024 00:43